How does Lokta isolate data between my partner lenders?

Tenant isolation by client_id runs through every record: cases, messages, knowledge base, audit logs, dashboards, and analytics. An agent assigned to Partner A only sees Partner A's queue; the AI's retrieval is scoped to Partner A's SOPs and verbatim templates; analytics never mix volumes across lenders. New partners are added through configuration, not code, so each onboarding is a setup task rather than a release.

What does 'lending-native classification' actually mean?

Triage understands the entities and lifecycle stages specific to lending (KYC, disbursement, repayment, NACH/ECS, foreclosure, hardship, settlement) and what each issue looks like at each stage of the loan. Tag 1 (partner + journey stage) → Subtag 1 (issue category) → Subtag 2 (intent), resolved at ingest in under a second across 40+ lending-specific intents. Generic CX tools start with retail categories and bolt lending on; Lokta starts at the LMS.

How does Lokta support compliance review?

Every AI interaction is logged with confidence score, tools used, retrieved evidence, and human override to support reviewability. PII (Aadhaar, PAN, IFSC, bank account, mobile, email) is masked at ingest before reaching any model. Verbatim compliance templates can be cited by the AI but never paraphrased. Confidence below the configured threshold holds the response for human approval before the borrower sees it. The lender and LSP remain responsible for regulatory interpretation, policy, approvals, oversight, and conduct.

Do partner books need to move onto Lokta?

Yes. The Lokta platform is the system of record and the system of intelligence for every partner book: the loans sit on Lokta's Loan Ledger and Accounting Ledger, isolated by partner, and the servicing agent works on them there. Each partner's book moves across through a migration that maps the accounts, reconciles balances and cuts over once they tie out. Your LOS, bureau and partner systems connect through MCP servers, one per system, without custom connectors, and the same MCPs can power your customer-facing chatbot.

How autonomous is the AI, and can I dial it back?

Three modes per channel, per partner: shadow (AI logs draft responses but humans send), copilot (AI drafts, human reviews and sends), and selective automation (AI sends when confidence clears your threshold). Most LSPs start in shadow on a new partner, move to copilot once accuracy is stable, and graduate channel-by-channel to selective automation as trust builds. You can dial it back at any time, per channel, per partner, without redeploying.

For loan service providers

AI loan servicing for LSPs

Bring the partner loan record, borrower conversation and next action into one workbench. Policy boundaries, approvals and the audit trail stay with each lender’s book.

Talk to us See how a day runs →

Multilender from day one
40+lending-specific intents
<1ssync triage
Reviewableaudit trail by default

How a day looks

From channel to closed ticket, without tab-switching.

01
Day 0
Setup
Connect your inbound channels. Map your partners' email domains. Wire your LOS and CRM via MCP. Import your FAQs: the AI starts learning from real tickets immediately.
02
Daily ops
Run
Borrower writes in → resolved to the right partner → classified by lifecycle stage and intent → loan and borrower context auto-attached → agent sees a draft reply with confidence score and the SOPs it cited → reviews → sends.
03
Continuous
Learn
The Knowledge Harvester surfaces SOP gaps from your unanswered tickets. Analytics segment by partner, channel, intent, and SLA, without mixing data across lenders.

The LSP reality

Servicing loans across multiple lenders is its own discipline.

Generic helpdesks weren't designed for this. Generic AI doesn't understand your policies. Building it in-house pulls engineering away from origination.

Without Lokta

Tribal knowledge trapped in tenured agents
Tickets sprawl across WhatsApp, email, phone, portal, Slack
Compliance teams chase evidence you can't assemble
Generic helpdesks ignore your partner taxonomy
In-house builds pull engineering from origination

With Lokta

Tenant-isolated by client_id: every record, every log
One workbench for every partner channel
Audit trail captured on every interaction
Lending-aware triage out of the box
Ship the playbook, not the platform

Lokta is different: agent-native and lending-native, multi-partner from day one, and engineered around the way LSPs actually operate.

New to the terminology? LOS vs LMS vs LSP sets out how an LSP differs from the origination and servicing systems it runs on.

Three pillars

Why LSPs choose Lokta.

Multi-partner from the core

Each partner book sits on Lokta’s ledgers, and tenant isolation by client_id runs through every record: loan accounts, cases, messages, knowledge, audit logs, dashboards. Add a new partner without changing code.

Lending-native intelligence

Triage understands KYC, disbursement, repayment, NACH/ECS, foreclosure, hardship, settlement, and what those look like at each lifecycle stage. Not retrofitted from generic CX.

Compliance-first AI

Every AI decision is logged with confidence, tools used, and human override. PII is masked. Verbatim templates can't be rewritten by an LLM. Humans approve before borrowers see the response.

Built for LSP workflows

Six capabilities engineered for multi-partner servicing.

Partner-aware pre-triage

Inbound emails route to the right partner deterministically, before any AI runs. Borrower phone numbers and IDs resolve the rest. Your agents see only their partner's queue.

Three-level classification, lending taxonomy

Tag 1 (partner + journey stage) → Subtag 1 (issue category) → Subtag 2 (intent). 40+ lending-specific intents, classified synchronously in under a second. Routing decisions happen at intake, not after.

MCP-first integrations

One MCP server per LOS, bureau, CRM or partner system, without writing custom connectors. Loan and borrower context comes from the partner books held on Lokta's ledgers. The same MCPs can power your customer-facing chatbot and your support agent's tools.

Multilingual borrower self-service

WhatsApp, email, and portal bots that detect Hindi, Hinglish, English, and major regional languages, and respond in kind. Foreclosure quotes, statement requests, payment troubleshooting, NACH status: all handled before a human is needed.

Per-partner SOPs and ground rules

A unified knowledge base scoped by partner, product, and lifecycle stage. Verbatim-tagged compliance templates the AI can reference but never rewrite. The system flags KB gaps from real ticket volume so your SOPs evolve with your operation.

Configurable autonomy per channel

Shadow (AI logs only) → Copilot (AI drafts, human sends) → Selective Automation (AI sends when confidence clears your threshold). Toggle per channel, per partner. Loosen as you build trust.

Trust & compliance

Built around RBI's Digital Lending Guidelines.

An LSP answers to its lending partner as well as to the regulator. Every agent action carries the record both of them ask for, on the same trail.

audit.log · case #LD-21884RBI · DLG · live

08:42:14.221  Audit       ✓  Every model call, tool use, data access, and human override logged.
08:42:14.224  PII-mask    ✓  Aadhaar, PAN, IFSC, bank account, mobile, email, masked at ingest.
08:42:14.226  Guardrail   ✓  Prompt-injection / jailbreak attempt blocked before reaching agents.
08:42:14.231  Template    ✓  Verbatim / locked compliance text, AI can reference, never paraphrase.
08:42:14.234  Human-gate  ✓  Confidence below threshold: held for human approval.

Even five years from now, we won't trust AI 100%. The conversation is always visible.
. Lokta product principle

Frequently asked

Questions LSPs ask before the demo.

How does Lokta isolate data between my partner lenders?
Tenant isolation by client_id runs through every record: cases, messages, knowledge base, audit logs, dashboards, and analytics. An agent assigned to Partner A only sees Partner A's queue; the AI's retrieval is scoped to Partner A's SOPs and verbatim templates; analytics never mix volumes across lenders. New partners are added through configuration, not code, so each onboarding is a setup task rather than a release.
What does 'lending-native classification' actually mean?
Triage understands the entities and lifecycle stages specific to lending (KYC, disbursement, repayment, NACH/ECS, foreclosure, hardship, settlement) and what each issue looks like at each stage of the loan. Tag 1 (partner + journey stage) → Subtag 1 (issue category) → Subtag 2 (intent), resolved at ingest in under a second across 40+ lending-specific intents. Generic CX tools start with retail categories and bolt lending on; Lokta starts at the LMS.
How does Lokta support compliance review?
Every AI interaction is logged with confidence score, tools used, retrieved evidence, and human override to support reviewability. PII (Aadhaar, PAN, IFSC, bank account, mobile, email) is masked at ingest before reaching any model. Verbatim compliance templates can be cited by the AI but never paraphrased. Confidence below the configured threshold holds the response for human approval before the borrower sees it. The lender and LSP remain responsible for regulatory interpretation, policy, approvals, oversight, and conduct.
Do partner books need to move onto Lokta?
Yes. The Lokta platform is the system of record and the system of intelligence for every partner book: the loans sit on Lokta's Loan Ledger and Accounting Ledger, isolated by partner, and the servicing agent works on them there. Each partner's book moves across through a migration that maps the accounts, reconciles balances and cuts over once they tie out. Your LOS, bureau and partner systems connect through MCP servers, one per system, without custom connectors, and the same MCPs can power your customer-facing chatbot.
How autonomous is the AI, and can I dial it back?
Three modes per channel, per partner: shadow (AI logs draft responses but humans send), copilot (AI drafts, human reviews and sends), and selective automation (AI sends when confidence clears your threshold). Most LSPs start in shadow on a new partner, move to copilot once accuracy is stable, and graduate channel-by-channel to selective automation as trust builds. You can dial it back at any time, per channel, per partner, without redeploying.

See it live

See Lokta on your own ticket data.

Reconciling repayments and payouts across several partner lenders is covered on multi-lender servicing.

30-minute demo. We'll triage a real sample of your tickets, show partner-aware routing live, and walk through how your team would use the workbench.